Reviewing Digital Manufacturing concept in the Industry 4.0 paradigm

Digitalization of manufacturing is once again on the industry application research agenda and Digital Manufacturing plays a fundamental role in this process. However, there is a lack of commonality in the literature about the purpose of Digital Manufacturing. The purpose of this paper is to analyze the concept and application domain of Digital Manufacturing considering the increasingly established Industry 4.0 paradigm. Based on a content analysis concepts are framed, and new technological characteristics identified. The paper contributes to a better understanding of the future challenges that companies face by positioning Digital Manufacturing conceptually and delimiting its application domain

An approach to open virtual commissioning for component-based automation

Increasing market demands for highly customised products with shorter time-to-market and at lower prices are forcing manufacturing systems to be built and operated in a more efficient ways. In order to overcome some of the limitations in traditional methods of automation system engineering, this thesis focuses on the creation of a new approach to Virtual Commissioning (VC). In current VC approaches, virtual models are driven by pre-programmed PLC control software. These approaches are still time-consuming and heavily control expertise-reliant as the required programming and debugging activities are mainly performed by control engineers. Another current limitation is that virtual models validated during VC are difficult to reuse due to a lack of tool-independent data models. Therefore, in order to maximise the potential of VC, there is a need for new VC approaches and tools to address these limitations. The main contributions of this research are: (1) to develop a new approach and the related engineering tool functionality for directly deploying PLC control software based on component-based VC models and reusable components; and (2) to build tool-independent common data models for describing component-based virtual automation systems in order to enable data reusability. [Continues.

The three-stage entrepreneurial model to empower recycling product designers.

Two of every five Egyptian youth aged 20-24 suffer unemployment and abject poverty. And while 40% of Egyptians have entrepreneurial intentions only 2.9% manage to establish their businesses past the 3.5-year mark of regulated operation. The main reasons for this failure have been defined to be: the poor entrepreneurial education at all stages, the poor legal &commercial infrastructure, as well as lack of supportive government programmes. The proposed solution is a three-stage process; it begins with formulating a ‘matrix model’, which is a detailed workplan for the transfer of an entrepreneurial idea from concept to a sustainable business, then developing a successful alpha product line that would allow business operation &sustenance, and then giving room for research and development of new similar products by incubating entrepreneurial ideas that can be turned into profitable product lines later on. The matrix model is the product-customised version of “Egyptian Ecosystem Theory of Change” by Saeed et al, 2015. The alpha product proposed is a flooring tile created from cleaned and shredded trash at the AUC Sustainable Development labs by heat-pressing plastics as a binder and redbrick as a filler, to create an environmentally friendly product line, then the tile is set to be tested against relevant ASTM standards for flooring tiles. Then, the proposed business model is to use part of the revenue to sponsor research and development, provided it is based on the ‘private incubator’ model. The idea is seen to positively impact the society by providing employment for the young entrepreneurs, the economy by boosting production and investment opportunities, as well as the environment by encouraging a recycling economy. This conforms with sustainable development goal number 8.6 which promotes substantially reducing the proportion of youth not in employment, education or training

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

Global dynamic E-marketplaces, and their role in the internet-based economy

Collaboration capabilities are what will most probably create the gap between winners and losers in business-to-business (B2B) commerce. In this context, the electronic marketplace (EM) comes as a medium for trade and collaboration, and a common entry point where partners can share business processes and adopt a decentralized business model fuelled by market evolution. The thesis illustrates the advantages of collaborative business and presents the information technologies that support it. The purpose of this thesis is to educate both the author and the reader on the technology and infrastructure that supports collaborative business and to posit that among the three major information technology infrastructures that enable B2B commerce, the EM model provides significant advantages for individual companies and industries compared to Electronic Data Interchange (EDI) and Peer-to-Peer (P2P). The thesis identifies key tools and value-added services EM\u27s should provide their participants to meet the requirements of modern companies and the Internet-based economy. Finally, the thesis suggests potential impacts of EM\u27s on the modern business ecosystem

Development of a Digital Twin of a Flexible Manufacturing System for Assisted Learning

Learning Factories provide a propitious learning environment for nurturing production related competencies. However, several problems continue to plague their widespread adoption. Further, assessment of attained competencies continue to remain a concern. This study proposes the use of digital twins as an alternative learning platform for production engineering courses. It is proposed that in the context of manufacturing pedagogy, digital twins of manufacturing processes can play a significant role in delivering efficacious learning experiences. The high-fidelity replication of the physical system aids with reflective observation of the entailed processes in the greatest possible detail, fostering concrete learning experiences. An iterative research methodology towards modelling a pedagogic digital twin is undertaken to build a learning environment that is characterized by ontologies that model learning objectives, learning outcomes and assessment of the said outcomes. This environment facilitates automated assessment of the learner via ontological reasoning mechanisms. The underlying schema takes into account the learner’s profile and focuses on competency attainment through reasoning of behavioural assessment of aligned learning outcomes. The thesis presents also a case study that demonstrates how the learner’s competency level may be evaluated and compared with other learners thus warranting its use a learning tool that proves beneficial in an academic setting

Development of an open source web-based infrastructure for designing medical devices

The term ‘Open Source’ is commonly associated with software due to its proven success, encompassing a user’s ability to review and modify the underlying source code, to disseminate modified or unmodified versions to others, and to use it without facing the prospect of legal repercussions (Siedlok, 2001). In the context of product design, namely medical device design, the concept remains relatively novel with no prior research being reported. A study of applying the open source concept to medical device design by developing a web based infrastructure for its facilitation is reported here. Results: The stakeholder requirements are captured using a semi-structured questionnaire and validated through cross referencing responses to questions with other responses from stakeholders of the same or similar occupation. The most prominent responses are selected as the key stakeholder requirements and utilised in conjunction with the functional system requirements outlined in the System Requirements Specification (SyRS), both sets of requirements provide the foundation for the open source web based infrastructure development. Conclusion: The comprehensiveness of the requirements indicate that the open source web based infrastructure will support the design of all medical devices that are classified as high risk, medium risk or low risk devices, whilst devices external to this scope remain a future certainty

An industrial analytics methodology and fog computing cyber-physical system for Industry 4.0 embedded machine learning applications

Industrial cyber-physical systems are the primary enabling technology for Industry 4.0, which combine legacy industrial and control engineering, with emerging technology paradigms (e.g. big data, internet-of-things, artificial intelligence, and machine learning), to derive self-aware and self-configuring factories capable of delivering major production innovations. However, the technologies and architectures needed to connect and extend physical factory operations to the cyber world have not been fully resolved. Although cloud computing and service-oriented architectures demonstrate strong adoption, such implementations are commonly produced using information technology perspectives, which can overlook engineering, control and Industry 4.0 design concerns relating to real-time performance, reliability or resilience. Hence, this research compares the latency and reliability performance of cyber-physical interfaces implemented using traditional cloud computing (i.e. centralised), and emerging fog computing (i.e. decentralised) paradigms, to deliver real-time embedded machine learning engineering applications for Industry 4.0. The findings highlight that despite the cloud’s highly scalable processing capacity, the fog’s decentralised, localised and autonomous topology may provide greater consistency, reliability, privacy and security for Industry 4.0 engineering applications, with the difference in observed maximum latency ranging from 67.7% to 99.4%. In addition, communication failures rates highlighted differences in both consistency and reliability, with the fog interface successfully responding to 900,000 communication requests (i.e. 0% failure rate), and the cloud interface recording failure rates of 0.11%, 1.42%, and 6.6% under varying levels of stress